Drug and Clinical Candidate Drug Data in ChEMBL

ChEMBL is a large-scale, open-access, FAIR database of bioactive molecules with drug-like properties. ChEMBL 35 contains 17,500 approved drugs, and drugs that are progressing through the clinical development pipeline. Drug curation has formed an integral part of the core offering of the ChEMBL database since its inception. The paper is a reference guide to present the principles of why the ChEMBL drug data has been curated in a particular manner so that data users can better understand the nature of the data. The drug data include information on: names, synonyms and trade names, chemical structure or biological sequence, data sources, indications, mechanisms, warnings and drug properties such as maximum phase of development, type of molecule, prodrug status and first approval. The integrated nature of the drug data within the context of a bioactivity resource enables the wide use of the data set in drug discovery, AI and machine learning.

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Publication Details

Journal
Journal of Medicinal Chemistry
Published
2025-09-19
DOI
https://doi.org/10.1021/acs.jmedchem.5c00920
Citations
6
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
9.03
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article

Drug and Clinical Candidate Drug Data in ChEMBL

Eloy Félix, Fiona Hunter, Noel M. O’Boyle, Andrew R. Leach et al.
6 citations
Journal of Medicinal Chemistry
Computational Drug Discovery Methods
9.03
article

Drug and Clinical Candidate Drug Data in ChEMBL

Eloy Félix, Fiona Hunter, Noel M. O’Boyle, Andrew R. Leach, Sybilla Corbett, María Paula Magariños, Harris Ioannidis, Barbara Zdrazil, Nicolas Bosc, Ines Smit, Marleen De Veij, A. Patrícia Bento, Emma J. Manners
article en
6 citations

Abstract

ChEMBL is a large-scale, open-access, FAIR database of bioactive molecules with drug-like properties. ChEMBL 35 contains 17,500 approved drugs, and drugs that are progressing through the clinical development pipeline. Drug curation has formed an integral part of the core offering of the ChEMBL database since its inception. The paper is a reference guide to present the principles of why the ChEMBL drug data has been curated in a particular manner so that data users can better understand the nature of the data. The drug data include information on: names, synonyms and trade names, chemical structure or biological sequence, data sources, indications, mechanisms, warnings and drug properties such as maximum phase of development, type of molecule, prodrug status and first approval. The integrated nature of the drug data within the context of a bioactivity resource enables the wide use of the data set in drug discovery, AI and machine learning.

Journal of Medicinal ChemistryVol. 68(19)
European Bioinformatics Institute (GB)
Openalex Percentile: Top 2%
Computational Drug Discovery Methods
9.03
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Drug and Clinical Candidate Drug Data in ChEMBL — Eloy Félix, Fiona Hunter, et al. · Journal of Medicinal Chemistry (2025) | TGRS Research Map | TGRS